Results for ade-graph

Core graph data structures and utilities for directed graphs.

Functions for generating various types of graph data, including complete and random graphs.

Graphics abstraction for Blade

Create evolving artistic images with hot-code-reloaded Lisp and GLSL.

Simple mixin for adding graph like functions (parents, children, traversal, etc) to any class. Effectively, you'll get DAG (directed acyclic graph) behaviour between your classes and therefore the ability to model parent, child and sibling behaviours with ease!

Creates the axes and gridlines for a graph in SVG. Perfect for creating a static background to which live data can be added.

ActiveRecord extension that turns your models into graph objects. Includes helper methods for adding <meta> tags and the Like Button to your views.

A lightweight Facebook Graph API client We have moved the development from rest-graph to [rest-core][]. By now on, we would only fix bugs in rest-graph rather than adding features, and we would only backport important changes from rest-core once in a period. If you want the latest goodies, please see [rest-core][] Otherwise, you can stay with rest-graph with bugs fixes. [rest-core]: https://github.com/cardinalblue/rest-core

Setup your Rails application with one or multiple clients for Azure AD Graph API using OAuth2 service-to-service calls.

llm-graph is a Ruby gem that provides verioned llm conversation graphs. It supports both directed and undirected graphs, and includes methods for adding and removing nodes and edges, checking for the existence of nodes and edges, and other common graph operations.

LegionIO identity provider that resolves Entra ID (Azure AD) identity via Microsoft Graph API into the unified identity contract

Transaction::Simple provides a generic way to add active transaction support to objects. The transaction methods added by this module will work with most objects, excluding those that cannot be Marshal-ed (bindings, procedure objects, IO instances, or singleton objects). The transactions supported by Transaction::Simple are not associated with any sort of data store. They are "live" transactions occurring in memory on the object itself. This is to allow "test" changes to be made to an object before making the changes permanent. Transaction::Simple can handle an "infinite" number of transaction levels (limited only by memory). If I open two transactions, commit the second, but abort the first, the object will revert to the original version. Transaction::Simple supports "named" transactions, so that multiple levels of transactions can be committed, aborted, or rewound by referring to the appropriate name of the transaction. Names may be any object except nil. Transaction groups are also supported. A transaction group is an object wrapper that manages a group of objects as if they were a single object for the purpose of transaction management. All transactions for this group of objects should be performed against the transaction group object, not against individual objects in the group. Version 1.4.0 of Transaction::Simple adds a new post-rewind hook so that complex graph objects of the type in tests/tc_broken_graph.rb can correct themselves. Version 1.4.0.1 just fixes a simple bug with #transaction method handling during the deprecation warning. Version 1.4.0.2 is a small update for people who use Transaction::Simple in bundler (adding lib/transaction-simple.rb) and other scenarios where having Hoe as a runtime dependency (a bug fixed in Hoe several years ago, but not visible in Transaction::Simple because it has not needed a re-release). All of the files internally have also been marked as UTF-8, ensuring full Ruby 1.9 compatibility.

In computer science, a disjoint-set data structure, also called a union–find data structure or merge–find set, is a data structure that keeps track of a set of elements partitioned into a number of disjoint (non-overlapping) subsets. It provides near-constant-time operations (bounded by the inverse Ackermann function) to add new sets, to merge existing sets, and to determine whether elements are in the same set. In addition to many other uses (see the Applications section), disjoint-sets play a key role in Kruskal's algorithm for finding the minimum spanning tree of a graph. A disjoint-set forest consists of a number of elements each of which stores an id, a parent pointer, and, in efficient algorithms, a value called the "rank". The parent pointers of elements are arranged to form one or more trees, each representing a set. If an element's parent pointer points to no other element, then the element is the root of a tree and is the representative member of its set. A set may consist of only a single element. However, if the element has a parent, the element is part of whatever set is identified by following the chain of parents upwards until a representative element (one without a parent) is reached at the root of the tree. Forests can be represented compactly in memory as arrays in which parents are indicated by their array index. Disjoint-set data structures model the partitioning of a set, for example to keep track of the connected components of an undirected graph. This model can then be used to determine whether two vertices belong to the same component, or whether adding an edge between them would result in a cycle. The Union–Find algorithm is used in high-performance implementations of unification. This data structure is used by the Boost Graph Library to implement its Incremental Connected Components functionality. It is also a key component in implementing Kruskal's algorithm to find the minimum spanning tree of a graph. Note that the implementation as disjoint-set forests doesn't allow the deletion of edges, even without path compression or the rank heuristic. Sharir and Agarwal report connections between the worst-case behavior of disjoint-sets and the length of Davenport–Schinzel sequences, a combinatorial structure from computational geometry.

GQLite is a Rust-language library, with a C interface, that implements a small, fast, self-contained, high-reliability, full-featured, Graph Query database engine. GQLite support multiple database backends, such as SQLite and redb. This enable to achieve high performance and for application to combine Graph queries with traditional SQL queries. GQLite source code is license under the [MIT License](LICENSE) and is free to everyone to use for any purpose. The official repositories contains bindings/APIs for C, C++, Python, Ruby and Crystal. The library is still in its early stage, but it is now fully functional. Development effort has now slowed down and new features are added on a by-need basis. It supports a subset of OpenCypher, with some ISO GQL extensions. Example of use -------------- ```ruby require 'gqlite' begin # Create a database on the file "test.db" connection = GQLite::Connection.new filename: "test.db" # Execute a simple query to create a node and return all the nodes value = connection.execute_oc_query("CREATE () MATCH (n) RETURN n") # Print the result if value.nil? puts "Empty results" else puts "Results are #{value.to_s}" end rescue GQLite::Error => ex # Report any error puts "An error has occured: #{ex.message}" end ``` The documentation for the GQL query language can found in [OpenCypher](https://auksys.org/documentation/5/libraries/gqlite/opencypher/) and for the [API](https://auksys.org/documentation/5/libraries/gqlite/api/).

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